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Share of births that are twins

See all data and research on:
Fertility Rate

What you should know about this indicator

  • Twin births have risen dramatically since the 1980s. One reason is the use of reproductive technologies such as in vitro fertilization (IVF), which have made it possible for many more couples to conceive. During procedures like IVF, multiple eggs can be used at the same time to maximize the chances of a successful pregnancy, which can lead to twin births.
  • Another reason for the rise in twin births is that the average age of women at childbirth has risen. Older women are more likely to have twin births, even without using reproductive technologies.
  • In some countries, twin birth rates have dropped in recent decades, as reproductive technologies have shifted to using single-embryo transfers instead of multiple.
Share of births that are twins
The number of twin deliveries per 100 deliveries.
Source
Human Multiple Births Database (2024) – processed by Our World in Data
Last updated
November 26, 2024
Next expected update
May 2026
Date range
1815–2022
Unit
%

Sources and processing

This data is based on the following sources

Human Multiple Births Database

The frequency of twin births has significantly increased in developed countries, doubling since the 1970s (see Figure 1). Two main factors have contributed to this development, namely the rise in the use of medically assisted reproduction techniques, as well as a substantial increase in the mean age at childbearing (Pison et al., 2015). This 'boom' in the birth of twins constitutes a public health challenge, in that twins tend to have frailer health than singletons, at least during their early years. Compared to singletons, twins have lower birth weight, they tend to be born prematurely, and the deliveries are more complicated, all of which can potentially lead to long-term health problems. It is therefore important to understand better the causes of the increase in the twinning rate, as well as the variations across countries.

The Human Multiple Births Database (HMBD) gathers the number of twin births and the twinning rates for countries with reliable statistics. The database also provides statistics on other multiple births (i.e., triplets, quadruplets, etc.) whenever possible. Although their frequency has increased even more than that of twins, they still constitute a minority, as most multiple deliveries involve twins. A detailed description of the HMBD is available in this article (DOI: 10.4054/DemRes.2023.48.4).

Retrieved on
November 26, 2024
Retrieved from
https://www.twinbirths.org/en/data-metadata/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Human Multiple Births Database (2024). French Institute for Demographic Studies - INED (distributor). Extracted from: https://www.twinbirths.org (26/11/2024).
A detailed description of the HMBD is available in:
Torres, C., Caporali, A., & Pison, G. (2023). The Human Multiple Births Database (HMBD). Demographic Research, 48, 89–106. https://doi.org/10.4054/demres.2023.48.4
Country-level sources:

The frequency of twin births has significantly increased in developed countries, doubling since the 1970s (see Figure 1). Two main factors have contributed to this development, namely the rise in the use of medically assisted reproduction techniques, as well as a substantial increase in the mean age at childbearing (Pison et al., 2015). This 'boom' in the birth of twins constitutes a public health challenge, in that twins tend to have frailer health than singletons, at least during their early years. Compared to singletons, twins have lower birth weight, they tend to be born prematurely, and the deliveries are more complicated, all of which can potentially lead to long-term health problems. It is therefore important to understand better the causes of the increase in the twinning rate, as well as the variations across countries.

The Human Multiple Births Database (HMBD) gathers the number of twin births and the twinning rates for countries with reliable statistics. The database also provides statistics on other multiple births (i.e., triplets, quadruplets, etc.) whenever possible. Although their frequency has increased even more than that of twins, they still constitute a minority, as most multiple deliveries involve twins. A detailed description of the HMBD is available in this article (DOI: 10.4054/DemRes.2023.48.4).

Retrieved on
November 26, 2024
Retrieved from
https://www.twinbirths.org/en/data-metadata/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Human Multiple Births Database (2024). French Institute for Demographic Studies - INED (distributor). Extracted from: https://www.twinbirths.org (26/11/2024).
A detailed description of the HMBD is available in:
Torres, C., Caporali, A., & Pison, G. (2023). The Human Multiple Births Database (HMBD). Demographic Research, 48, 89–106. https://doi.org/10.4054/demres.2023.48.4
Country-level sources:

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

Data sometimes includes stillbirths, therefore comparability across countries should be done with care.

Countries including stillbirths: Czech Republic, Denmark, England and Wales, France, Greece, Italy, Lithuania, Netherlands, Norway, Spain, Sweden, Switzerland

Countries mostly including stillbirths: Austria (unknown for 1920, 1921, 1928, 1929, 1931, 1934), Canada (unknown for 1921-1925, 1927-1990), Finland (unknown for 1906-1936, 1941-1999), Germany (unknown for 1906-1936), Japan (unknown for 1923-1936)

Countries excluding stillbirths: Chile, South Korea

Countries with mixed practices: Australia, New Zealand (excluded for 1856-1915), United States, Scotland (excluded for 1856-1938), Uruguay

For more details about the data for a specific country, please refer to the original source.

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
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Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Share of births that are twins”, part of the following publication: Saloni Dattani, Lucas Rodés-Guirao, and Max Roser (2025) - “Fertility Rate”. Data adapted from Human Multiple Births Database. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/rate-of-twin-deliveries.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Human Multiple Births Database (2024) – processed by Our World in Data

Full citation

Human Multiple Births Database (2024) – processed by Our World in Data. “Share of births that are twins” [dataset]. Human Multiple Births Database, “Human Multiple Births Database v.1” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/rate-of-twin-deliveries.html (archived on March 4, 2026).

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Metadata URL (JSON format)
https://ourworldindata.org/grapher/rate-of-twin-deliveries.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/rate-of-twin-deliveries.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/rate-of-twin-deliveries.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/rate-of-twin-deliveries.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/rate-of-twin-deliveries.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/rate-of-twin-deliveries.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/rate-of-twin-deliveries.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear